Machine Learning Master's student at @UTokyo_News_en. Staying at @NTUSg from Jul-Dec '26. Intern at EQUES, @Matsuo_Lab. Prev: @MatsuoInstitute, IS23er.
Come to see our poster today!
🏟️Hall A, #3106
🕐4:45pm-5:30pm (but if you want to chat at a different time, drop me a message anytime via DM or ICML App!)
We present our paper "Mitigating Reward Hacking via Adversarial Robustness" at EIML@ICML2026!
We conjecture that reward hacking is often caused by flipped advantage-sign estimations, and propose SignCert-PO, a new algorithm built on the theory of randomized smoothing! 🧵
Update: I’m honored to have been selected as a Toyota Riken Overseas Predoctoral Fellow (OSPDF), which provides substantial support including tuition and living expenses.
I’m actively looking for Fall 2027 PhD positions in the following areas.
I’d be very happy to chat at ICML!
Thank you Johannes, it has been a real pleasure working with you!
I'm currently looking for PhD positions for Fall 2027. I'm with an ML background, interested in AI alignment, multi-agent RL, strategic decision making and more.
I'll be at ICML and would be very happy to chat!
Thank you Johannes, it has been a real pleasure working with you!
I'm currently looking for PhD positions for Fall 2027. I'm with an ML background, interested in AI alignment, multi-agent RL, strategic decision making and more.
I'll be at ICML and would be very happy to chat!
The lead author, @shinnosukeono, is also currently looking for PhD positions!
He is one of the most talented master's students I have had the pleasure of working with, I highly recommend him!
Come chat on Friday, July 10 at EIML@ICML2026, Seoul!🇰🇷
Joint work with @johannesack, @nissymori1, @tksii and Masashi Sugiyama.
https://t.co/k9Yr4teESz
We present our paper "Mitigating Reward Hacking via Adversarial Robustness" at EIML@ICML2026!
We conjecture that reward hacking is often caused by flipped advantage-sign estimations, and propose SignCert-PO, a new algorithm built on the theory of randomized smoothing! 🧵
Across model sizes and benchmarks, SignCert-PO performs well and prevents reward hacking. It holds back the policy from going unreliable regions, and this is done dynamically during optimization!
Then, we propose SignCert-PO, a new algorithm to handle this uncertainty. Using the theory of randomized smoothing, we show our algorithm results in a surprisingly simple form!